Some squatter who bought the rights to it for two twigs and a raspberry back when they were first selling off name rights 200,000 years ago

The raison d’être for RISC-V is domain-specific architecture. Currently, computational demands are growing exponentially (especially with AI), but Moore’s Law is ending, which means we can no longer meet our computational demands by scaling single-core speed on general-purpose CPUs. Instead, we are needing to create custom architectures for handling particular computational loads to eke out more performance. Things like NPUs, TPUs, etc.

The trouble is designing and producing these domain-specific architectures is expensive af, especially given the closed-source nature of computer hardware at the moment. And all that time, effort, and money just to produce a niche chip used for a niche application? The economics don’t economic.

But with an open ISA like RISC-V, it’s both possible and legal to do things like create an open-source chip design and put it on GitHub. In fact, several of those exist already. This significantly lowers the costs of designing domain-specific architectures, as you can now just fork an existing chip and make some domain-specific modifications/additions. A great example of this is PERCIVAL: Open-Source Posit RISC-V Core with Quire Capability. You could clone their repo and spin up their custom RISC-V posit chip on an FPGA today if you wanted to.

Yeah, this is the one piece a lot of people miss: in any decently competitive market, individual firms have effectively zero power to set prices; they must instead accept the prices determined by the market.

Knowing that, the solution to that sort of corporate BS, then, is to ensure markets are competitive by busting monopolies, lowering barriers to entry, and getting money out of politics to reduce the effect of lobbying.

You might like single transferrable vote (STV), then. You have districts with several seats in them (preferably ~5), and then do a ranked-choice ballot to select the candidates who will fill those seats. Key advantages over proportional representation are that it maintains the idea of a constituency and that it maintains voting for individual candidates, not just parties.

Downside, of course, is that it’s not as proportional as proportional representation, but it still achieves pretty proportional results. That’s the tradeoff for maintaining constituencies and individual candidates.

Sounds similar to some of the research my sister has done in her PhD so far. As I understand, she had a bunch of snapshots of proteins from a cryo electron microscope, but these snapshots are 2D. She used ML to construct 3D shapes of different types of proteins. And finding the shape of a protein is important because the shape defines the function. It’s crazy stuff that would be ludicrously difficult and time-consuming to try to do manually.

Exactly. I rode an ebike one summer to commute to an internship. The sweat factor alone meant I never would have done that by regular bike, as I would’ve arrived at the office sweating like a pig.

On the other hand, a car has far greater maintenance costs. The car has license, insurance, maintenance, gas, parking, etc., whereas an ebike is basically free in comparison. Electricity to power an ebike is pennies, and maintainance is a few basic tools and a new tire or inner tube on occasion.

With all the money saved, you can just rent a car for the handful of days the ebike genuinely is not sufficient.

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I moved from California to Montreal a few years back to study, and now I’m staying for good. I tried duolingo on and off for far too long, but I found it super uninteresting and hard to remain committed to.

Best strategy I’ve found is called comprehensible input. The idea is to find books or other reading material that you can get the basic gist of when reading, despite not understanding every single word and phrase and grammatical construction. The more you read, the more you’ll find yourself able to understand, which is also very motivsting!

Also, make sure it’s material that actually interests you. The idea is it’s better to read extensively, reading things that actually interest you to some degree and keep you mentally engaged, than to just really intensively study a much smaller amount of (less interesting) material.

This actually mirrors how we acquire languge. The idea is to intuitively understand French by having seen a lot of it rather than to basically memorize French. You ultimately want to be able to glance at a sign, for instance, and just know what it means without having to translate in your head.

Some resources I found useful were these French illustrated books in Dollarama, but even better is a series of books designed to be comprehensible input by Olly Richards. He’s a native English speaker and polyglot who has written a bunch of graded readers that gradually increase in vocabulary and difficulty. He has several books for French, including beginner short stories, intermediate short stories, beginner conversations, intermediate conversations, climate change, WW2, and philosophy. The nice thing is he actually does a good job of making the stories and content interesting to an adult learner, unlike the children’s books at Dollarama.

Even his beginner books might be a little too advanced for your level so far, though, from what you say. If they are, it’d be best to find some material at a lower level that you can understand a little better. After all, if it’s too hard for you, it will make the process much slower and less enjoyable, which will make it much more likely that you quit. You could even simply try googling “french comprehensible input” to try to find material suitable for your level.

One last resource is the government of Quebec offers free in-person courses for immigrants and many French learners. They are part-time, and they offer multiple options for hours per week, so you could pick what works best for you. It would be worth checking to see if you might qualify for those courses once you move here.

Yeah, I’m working in embedded ML, and it’s an insanely exciting time. We’re getting more and more microcontrollers and single-board computers with special AI accelerators, many of them RISC-V, by the day it seems. One of the next steps (in my opinion) is finding a good way to program them that doesn’t involve C/C++ (very fast but also so painful to do AI with) or Python (slow unless it’s wrapping underlying C code, and unsuitable for microcontrollers). In fact, that’s exactly what I’m working on right now as a side project.

What’s also cool is RISC-V promises to be the one instruction set architecture to rule them all. So instead of having PCs as x86, phones and microcontrollers as ARM, then all sorts of other custom architectures like DSPs (digital signal processors), NPUs, etc., we could just have RISC-V with a bunch of open standard extensions. Want vector instructions? Well, here’s a ratified open standard for vector instructions. Want SIMD instructions? Congrats, here’s another ratified open standard.

And all these standards mean it will make it so much easier for the compiler people to provide support for new chips. A day not too long from now, I imagine it will become almost trivial to compile programs that can accelerate tons of scientific, numerical, and AI workloads onto RISC-V vector instructions. Currently, we’re stuck using GPUs for everything that needs parallelization, even though they’re far from the easiest or most optimal devices for many of our computational needs.

As computing advances, we can just create and ratify new open standards. Tired of floating point numbers? You could create a proposal for a standard posit extension today if you wanted to, then fork LLVM or GCC or something to provide the software support as well. In fact, someone already has implemented an open-source RISC-V chip with posit arithmetic and made a fork of LLVM to support it. You could fire it up on an FPGA right now if you wanted.

This talk, given by David Patterson (a legend in computer architecture and one of the people who helped create RISC-V at UC Berkeley) is an excellent (and accessible) introduction.

It’s especially dumb because RISC-V is – dare I say it – inevitably the future. Trying to crack down on RISC-V is like trying to crack down on Linux or solar photovoltaics or wind turbines. That is, you can try to crack down, but the fundamental value proposition is simply too good. All you’ll achieve in cracking down is hurting yourself while everyone else gets ahead.

This video by a political science professor explains it best: https://youtu.be/zMxHU34IgyY?si=N5oHElN4Xlbiqznh

In short, the only people who truly know are Hamas, and the best the rest of us can do is speculate.

Some possibilities are that Hamas wanted to sabotage normalizing relations between Israel and the rest of the Muslim world, that Hamas wanted to bait Israel into a wildly disproportionate response that would garner themselves sympathy and recruits, that Hamas was bluffing and feigning strength and counting on Israel to think the attack was bait, that Hamas was just acting on bloodlust and wanted to attack regardless of the consequences, or many other possibilities.

Further, we focus a lot on the substative issues, i.e., the grievances and disagreements at hand, but we don’t talk about the bargaining frictions nearly enough. There are countless border disputes around the world, and yet they rarely result in war. Why? Because war is costly and most wish to avoid it. War typically happens when there are both substantive issues and bargaining frictions, i.e., things preventing the two sides from negotiating a solution. But us onlookers can’t even know for sure what these frictions are, only speculate.

All this is simply the nature of the fog of war, that the true strategies/goals won’t be known for a while, if ever. Anyone who tries to tell you with certainty why they did what they did at this stage doesn’t actually know with any degree of certainty. Nobody but Hamas actually knows.

I do recommend watching the full video above, as the professor is very engaging, rather amusing, and covers this topic quite thoroughly.

Yeah, it’s the expected outcome when you grant a group of people a monopoly on violence but with insufficient to non-existent incentives for good behavior and insufficient to non-existent disincentivizes for bad behavior.

And Chronic Wasting Disease (CWD) in cervids such as deer, moose, and elk, which thankfully has not been shown to be transmissible to humans yet. Prions are the stuff of nightmares.

Oh, and Fatal Familial Insomnia.

Definitely. If you don’t understand how the world works, you can’t tell if someone else does either. Only experts can easily spot fake experts. And that’s exactly the trouble with things like pseudoscience and misinformation; it’s easy to fall for without the domain knowledge necessary to avoid falling for it.

A great example is when you’re in elementary school and you get that one really athletic kid on your team for some team sport in gym class. You know you’re not on that level and never will be, so you tie yourself to them, knowing that them succeeding is good for you.

Likewise, we like to attach our fortunes to a designated person, and they become greater than just a person in our mind. Like, that athletic kid is not longer simply a kid who’s good at sports; they’re the athletic kid. Our favored 19th-century political thought leader is no longer just some person who had opinions on society and wrote them down; they’re a political messiah.

Yeah, I think we did

The type of biome you get depends largely on availability of water, not temperature.

Deserts are deserts because they have very poor availability of water most of the time. This is most often caused by simple lack of precipitation, but other factors can influence this:

• High temperatures cause high evaporation rates, meaning to need more precipitation to achieve the same level of plant growth. This is why, for example, 10 inches (25.4 cm) of precipitation will get you desert in the tropics, subtropics, and temperate latitudes, but it’ll get you boreal forest in the colder subpolar latitudes.
• Extremely low temperatures (such as in Antarctica) result in everything being perpetually frozen. Most of Antarctica is a desert, both because it gets very little precipitation and because all the ice on the ground isn’t available as liquid water.
• Extremely sandy or gravelly soils which do not retain water cause poor water availability, even with abundant precipitation and a mild climate. While these aren’t typically classified as "true deserts), the plant life certainly reflects the harsh conditions and poor availability of water.

As for why we largely don’t see desert at the equator, it’s because of precipitation. Due to the circulation of cold and warm air in the atmosphere, the equator typically sees warm air, often laden with moisture due to the oceans and the high moisture capacity of warm air, rise. As it rises, it cools, and because cool air cannot hold as much moisture as warm air can, it drops a lot of that moisture as rain. This results in most of the equator getting a lot of rain.

Once the air has risen and cooled, it cycles north and south into the subtropics, where it falls down to earth again. And in falling, it warms up again, especially as these regions still receive a ton of sunlight, particularly in the summer. But the air has already lost much of its moisture, so now it’s just a bunch of hot, dry air blasting down over the subtropics. This is why we have bands of deserts across most of the subtropics, from the Sahara to the Middle East to the desert of the SW US and northern Mexico. Same on the opposite side of the equator, with the Kalahari desert in southern Africa, the Australian outback, and the Patagonian desert.

There are other factors, too, of course, such as rain shadows from mountains and ocean currents, but the atmospheric circulation is the big one to answer your question.

They don’t just look like diamond; chemically they’re extremely similar, too. Diamond is just a bunch of carbon atoms covalently bonded together into a 3D crystal, which is why they’re so incredibly hard. Moissanite is basically the same but it’s carbon and silicon atoms mixed together. Silicon has the same number of valence electrons, so it can function similarly chemically as carbon, hence why it works. Thus, moissanite is also extremely hard and refracts light in beautiful ways, too, except imo even more beautifully. Instead of a colorless luster, it’s a subtle rainbow luster to moissanite.

Source: I got my fiancée a moissanite ring, and it’s lovely. And because it’s lab-made, I got her blue moissanite (the coloring is just from adding certain impurities) that matches our cat’s eyes perfectly. It’s way more unique, cheaper, and more ethical than diamond, but doesn’t sacrifice on quality one bit.